A positive autoregulatory loop required for the expression of the transcription factor Krox20 was dissected using in vivo quantitative data and biophysical modelling to demonstrate how Krox20 controls cell fate decision and rhombomere size in the hindbrain.
Positive autoregulation of Krox20 underpins a bistable switch that turns a transient input signal into cell fate commitment, as demonstrated in single cell analyses.The duration and strength of the input signal control the size of the hindbrain segments by modulating the distribution between two cell fates.The progressive extinction of Krox20 expression involves a destabilization of the loop by repressor molecules.
Although feedback loops are essential in development, their molecular implementation and precise functions remain elusive. Using enhancer knockout in mice, we demonstrate that a direct, positive autoregulatory loop amplifies and maintains the expression of Krox20, a transcription factor governing vertebrate hindbrain segmentation. By combining quantitative data collected in the zebrafish with biophysical modelling that accounts for the intrinsic stochastic molecular dynamics, we dissect the loop at the molecular level. We find that it underpins a bistable switch that turns a transient input signal into cell fate commitment, as we observe in single cell analyses. The stochasticity of the activation process leads to a graded input–output response until saturation is reached. Consequently, the duration and strength of the input signal controls the size of the hindbrain segments by modulating the distribution between the two cell fates. Moreover, segment formation is buffered from severe variations in input level. Finally, the progressive extinction of Krox20 expression involves a destabilization of the loop by repressor molecules. These mechanisms are of general significance for cell type specification and tissue patterning.
Fgf; Krox20; rhombomere; stochastic model; transcriptional enhancer
The development and progress in synthetic biology has been remarkable. Although still in its infancy, synthetic biology has achieved much during the past decade. Improvements in genetic circuit design have increased the potential for clinical applicability of synthetic biology research. What began as simple transcriptional gene switches has rapidly developed into a variety of complex regulatory circuits based on the transcriptional, translational and post-translational regulation. Instead of compounds with potential pharmacologic side effects, the inducer molecules now used are metabolites of the human body and even members of native cell signaling pathways. In this review, we address recent progress in mammalian synthetic biology circuit design and focus on how novel designs push synthetic biology toward clinical implementation. Groundbreaking research on the implementation of optogenetics and intercellular communications is addressed, as particularly optogenetics provides unprecedented opportunities for clinical application. Along with an increase in synthetic network complexity, multicellular systems are now being used to provide a platform for next-generation circuit design.
gene circuits; mammalian designer devices; synthetic biology
The contribution of transcription, protein synthesis and degradation rates to the control of protein expression during differentiation was analyzed using quantitative proteomics and transcriptomics data. Protein synthesis rate was identified as the main determinant of protein expression.
The lack of correlation usually observed between transcript and protein levels can be fully explained when correcting for the synthesis and degradation rates of the individual proteins.Synthesis rates for individual proteins are extensively regulated, in contrast to degradation rates that mostly remain constant in response to differentiation.The modularity of macromolecular complexes is maintained during synthesis and degradation of the complexes.
External perturbations, by forcing cells to adapt to a new environment, often elicit large-scale changes in gene expression resulting in an altered proteome that improves the cell's fitness in the new conditions. Steady-state levels of a proteome depend on transcription, the levels of transcripts, translation and protein degradation but system-level contribution that each of these processes make to the final protein expression change has yet to be explored. We therefore applied a systems biology approach to characterize the regulation of protein expression during cellular differentiation using quantitative proteomics. As a general rule, it seems that protein expression during cellular differentiation is largely controlled by changes in the relative synthesis rate, whereas the relative degradation rate of the majority of proteins stays constant. In these data, we also observe that the proteins in defined sub-structures of larger protein complexes tend to have highly correlated synthesis and degradation rates but that this does not necessarily extend to the holo-complex. Finally, we provide strong evidence that the generally poor correlation observed between transcript and protein levels can fully be explained once the protein synthesis and degradation rates are taken into account.
differentiation; macromolecular complexes; protein turnover; proteomics; systems biology
A map of cell type-specific auxin responses
The transcriptional response to auxin was analyzed in four root cell types. The newly obtained data were cross-referenced with spatial expression maps to examine auxin's role in regulating gene expression in the root meristem.
The majority of the thousands of auxin-responsive genes in the Arabidopsis thaliana root show a spatial bias in their induction or repression by auxin treatment.Auxin promotes the expression of cell-identity markers for the developing xylem and quiescent center, whereas it inhibits markers for the maturing xylem, cortex and trichoblasts.Relative induction or repression by auxin predicts expression along the longitudinal axis of the root.
In plants, changes in local auxin concentrations can trigger a range of developmental processes as distinct tissues respond differently to the same auxin stimulus. However, little is known about how auxin is interpreted by individual cell types. We performed a transcriptomic analysis of responses to auxin within four distinct tissues of the Arabidopsis thaliana root and demonstrate that different cell types show competence for discrete responses. The majority of auxin-responsive genes displayed a spatial bias in their induction or repression. The novel data set was used to examine how auxin influences tissue-specific transcriptional regulation of cell-identity markers. Additionally, the data were used in combination with spatial expression maps of the root to plot a transcriptomic auxin-response gradient across the apical and basal meristem. The readout revealed a strong correlation for thousands of genes between the relative response to auxin and expression along the longitudinal axis of the root. This data set and comparative analysis provide a transcriptome-level spatial breakdown of the response to auxin within an organ where this hormone mediates many aspects of development.
Arabidopsis; development; root apical meristem; signaling gradient
The existence and nature of an active chromosome segregation apparatus in bacteria has been a long-standing debate. A novel Brownian ratchet-type mechanism of chromosome segregation mediated by the Min system is identified in E. coli.
Numerical simulations show that entropy alone is not sufficient to complete segregation of bacterial chromosomes.Chromosome segregation can be enhanced by a polar gradient of DNA tethering sites on the membrane.The cell-division regulator MinD forms a polar gradient on the membrane and binds DNA in an ATP-dependent manner.The bacterial Min system coordinates cell division and chromosome segregation.
The mechanisms underlying chromosome segregation in prokaryotes remain a subject of debate and no unifying view has yet emerged. Given that the initial disentanglement of duplicated chromosomes could be achieved by purely entropic forces, even the requirement of an active prokaryotic segregation machinery has been questioned. Using computer simulations, we show that entropic forces alone are not sufficient to achieve and maintain full separation of chromosomes. This is, however, possible by assuming repeated binding of chromosomes along a gradient of membrane-associated tethering sites toward the poles. We propose that, in Escherichia coli, such a gradient of membrane tethering sites may be provided by the oscillatory Min system, otherwise known for its role in selecting the cell division site. Consistent with this hypothesis, we demonstrate that MinD binds to DNA and tethers it to the membrane in an ATP-dependent manner. Taken together, our combined theoretical and experimental results suggest the existence of a novel mechanism of chromosome segregation based on the Min system, further highlighting the importance of active segregation of chromosomes in prokaryotic cell biology.
computer simulations; chromosome segregation; DNA binding; MinD; Min system
In higher eukaryotes, chromatin limits the transmission of transcriptional noise by insulating downstream genes from cell-to-cell variations in transcription factor heterodimers. In addition, heterodimers are shown to exhibit reduced cell-to-cell variation compared to their parent mRNAs.
The numbers of mRNA molecules encoding c-fos and c-jun do not correlate with each other in individual cells.The numbers of c-fos and c-jun heterodimers vary little compared to their parent mRNAs.Transcription of downstream genes is intrinsically noisy but there is little or no transmission of noise from the upstream steps.
We explored how transcriptional noise propagates in gene-regulatory pathways by studying the induction of two downstream genes by transcription factors c-fos and c-jun. They are produced for a brief period following serum stimulation of cells and then activate the promoters of their target genes by binding to them as heterodimers. We found that, even though they are coordinately expressed at the population level, in individual cells the expression of c-fos and c-jun is noisy and uncorrelated with each other. The expression of the downstream genes is also noisy, but there is little or no effect of the noise in the upstream genes on the expression of the downstream genes. The noise is not transmitted, because the number of heterodimers present in single cells is relatively invariant, and the induction of downstream genes is insensitive to the number of heterodimers in individual cells. Sequestration of promoters of the downstream genes within compact chromatin is a likely cause of this insensitivity. These barriers to the propagation and amplification of noise are likely to be commonplace in higher eukaryotes.
cellular heterogeneity; noise in gene expression; transcription
A general bacterial genome engineering framework, ‘Genome Editing via Targetrons and Recombinases' (GETR), is presented. GETR combines mobile group II introns (targetrons) and the Cre/lox system to allow genomic manipulations at a large scale.
The combination of targetrons and Cre/lox represents a broad-host range solution to genome editing.Engineered targetrons were used to deliver lox sites site-specifically into the bacterial genome.Targetrons carrying lox sites were used to generate large-scale insertions, deletions, inversions, and unique cut-and-paste operations in bacterial genomes.
Efficient bacterial genetic engineering approaches with broad-host applicability are rare. We combine two systems, mobile group II introns (‘targetrons') and Cre/lox, which function efficiently in many different organisms, into a versatile platform we call GETR (Genome Editing via Targetrons and Recombinases). The introns deliver lox sites to specific genomic loci, enabling genomic manipulations. Efficiency is enhanced by adding flexibility to the RNA hairpins formed by the lox sites. We use the system for insertions, deletions, inversions, and one-step cut-and-paste operations. We demonstrate insertion of a 12-kb polyketide synthase operon into the lacZ gene of Escherichia coli, multiple simultaneous and sequential deletions of up to 120 kb in E. coli and Staphylococcus aureus, inversions of up to 1.2 Mb in E. coli and Bacillus subtilis, and one-step cut-and-pastes for translocating 120 kb of genomic sequence to a site 1.5 Mb away. We also demonstrate the simultaneous delivery of lox sites into multiple loci in the Shewanella oneidensis genome. No selectable markers need to be placed in the genome, and the efficiency of Cre-mediated manipulations typically approaches 100%.
bacterial genome engineering; Cre-lox; mobile group II introns; Staphylococcus aureus; Shewanella oneidensis
The evolution of cooperation in colonies of swarming bacteria is analyzed by manipulating the cost-to-benefit ratio of cooperation to show that ‘constitutive' cooperation is favored only when relatedness is high, in contrast to ‘prudent' cooperation.
Swarming in the bacterium Pseudomonas aeruginosa is a cooperative trait that is beneficial for the group, as it allows colony expansion.Constitutive swarming cooperation is costly to cooperating individuals and has diminishing returns, but can still be favored by multilevel selection if relatedness is high.Swarming cooperation is favored in a wider range of conditions when regulated by metabolic prudence.
The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge.
conflict; cooperation; metabolic prudence; Pseudomonas aeruginosa; swarming
A combined cross-platform approach is presented to experimentally identify and characterize interactions between mouse transcription factors and regulatory elements at unprecedented resolution and throughput.
We generated a mouse-specific transcription factor (TF) library consisting of 750 full-length sequence-verified open-reading frame clones.We used this resource to develop a cross-platform pipeline to experimentally characterize mammalian regulatory elements of interest for interacting TFs at unprecedented throughput and resolution.Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers novel TF–DNA interactions that are relevant in vivo.
The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein–DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF–DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers.
gene regulatory networks; microfluidics; mouse open-reading frame (ORF) clone collection; transcription factor; yeast one-hybrid
Analysis of the cooperative nature of antibiotic inactivation reveals factors enabling coexistence of resistant and sensitive cells, showing that social interactions affect the spread of antibiotic resistance.
Inactivation of β-lactam antibiotics by resistant bacteria is a cooperative behavior that enables sensitive bacteria to survive antibiotic treatment.At high cell densities, resistant cells protect sensitive cells against antibiotic concentrations that are 100-fold higher than the minimum inhibitory concentration of sensitive cells.Eventually, the fraction of resistant cells in a bacterial population reaches an equilibrium fraction that depends on the initial cell density and antibiotic concentration.The addition of a commonly used β-lactamase inhibitor can lead to the spread of resistance in the population.
Inactivation of β-lactam antibiotics by resistant bacteria is a ‘cooperative' behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a β-lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used β-lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance.
antibiotic inactivation; antibiotic resistance; cooperation and cheating; β-lactam; population dynamics
Quantitative measurement of proteins involved in insulin signaling and central metabolism in C57BL/6J and 129Sv mice subjected to a sustained high-fat diet reveals that the two strains diverge early in their response to the feeding regimen.
Quantitative targeted protein measurements were designed to quantify murine proteins covering the insulin-signaling pathway
and the lipid and carbohydrate metabolism and used to compare the differential effect of a persistent high-fat diet in C57BL/6J
and 129Sv mouse strains.Differential effect of a persistent high-fat diet were compared in C57BL/6J and 129Sv mouse strains.Differences in protein abundances suggest that peroxisomal β-oxidation is actively promoted in fatty C57BL/6J mice whereas
lipogenesis activation dominates the response of 129Sv mice.Most strain-specific changes were apparent early in the regimen when phenotypic changes were already set, but not yet very
pronounced and they allow a clear discrimination of the mouse strains at an early stage during the long-term high-fat diet.Persistent high-fat diet also alters the transient changes that normally occur in C57BL/6J and 129Sv mice in response to fasting
or food intake.
The metabolic syndrome is a collection of risk factors including obesity, insulin resistance and hepatic steatosis, which occur together and increase the risk of diseases such as diabetes, cardiovascular disease and cancer. In spite of intense research, the complex etiology of insulin resistance and its association with the accumulation of triacylglycerides in the liver and with hepatic steatosis remains not completely understood. Here, we performed quantitative measurements of 144 proteins involved in the insulin-signaling pathway and central metabolism in liver homogenates of two genetically well-defined mouse strains C57BL/6J and 129Sv that were subjected to a sustained high-fat diet. We used targeted mass spectrometry by selected reaction monitoring (SRM) to generate accurate and reproducible quantitation of the targeted proteins across 36 different samples (12 conditions and 3 biological replicates), generating one of the largest quantitative targeted proteomics data sets in mammalian tissues. Our results revealed rapid response to high-fat diet that diverged early in the feeding regimen, and evidenced a response to high-fat diet dominated by the activation of peroxisomal β-oxidation in C57BL/6J and by lipogenesis in 129Sv mice.
liver; metabolic syndrome; NAFLD; proteomics; SRM
Quantitative proteomics, lifespan analysis, and biochemical assays were utilized to show that Insulin/IGF-1-mediated longevity in C. elegans is strongly associated with a daf-16 dependent global reduction in protein metabolism.
A daf-16 dependent global reduction in protein translation is observed in daf-2 long-lived mutant.The reduction in active translation is independent of germline activityA role for protein metabolism is identified in the Insulin/IGF-1-mediated extension of life.
Mutations in the daf-2 gene of the conserved Insulin/Insulin-like Growth Factor (IGF-1) pathway double the lifespan of the nematode Caenorhabditis elegans. This phenotype is completely suppressed by deletion of Forkhead transcription factor daf-16. To uncover regulatory mechanisms coordinating this extension of life, we employed a quantitative proteomics strategy with daf-2 mutants in comparison with N2 and daf-16; daf-2 double mutants. This revealed a remarkable longevity-specific decrease in proteins involved in mRNA processing and transport, the translational machinery, and protein metabolism. Correspondingly, the daf-2 mutants display lower amounts of mRNA and 20S proteasome activity, despite maintaining total protein levels equal to that observed in wild types. Polyribosome profiling in the daf-2 and daf-16;daf-2 double mutants confirmed a daf-16-dependent reduction in overall translation, a phenotype reminiscent of Dietary Restriction-mediated longevity, which was independent of germline activity. RNA interference (RNAi)-mediated knockdown of proteins identified by our approach resulted in modified C. elegans lifespan confirming the importance of these processes in Insulin/IGF-1-mediated longevity. Together, the results demonstrate a role for the metabolism of proteins in the Insulin/IGF-1-mediated extension of life.
ageing; high-throughput analysis; metabolism; protein metabolism; translation
The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype–phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large-scale network models with sufficient accuracy.
This review summarizes the applications enabled by genome-scale models of metabolism for the bacterium E. coli. It provides an overview of the applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field.
constraint-based modeling; Escherichia coli; metabolic engineering; metabolism; network reconstruction
Drug-induced transcriptional modules (biclusters) were identified and annotated in three human cell lines and rat liver. These were used to assess conservation across systems and to infer and experimentally validate novel drug effects and gene functions.
Biclustering of drug-induced gene expression profiles resulted in modules of drugs and genes, which were enriched in both drug and gene annotations.Identifying drug-induced transcriptional modules separately in three human cell lines and rat liver allows assessment of their conservation across model systems. About 70% of modules are conserved across cell lines, a lower bound of 15% was estimated for their conservation across organisms, and between the in vitro and in vivo systems.Drug-induced transcriptional modules can predict novel gene functions. A conserved module associated with (chole)sterol metabolism revealed novel regulators of cellular cholesterol homeostasis; 10 of them were validated in functional imaging assays.Analysis of drugs clustered into modules can give new insights into their mechanisms of action and provide leads for drug repositioning. We predicted and experimentally validated novel cell cycle inhibitors and modulators of PPARγ, estrogen and adrenergic receptors, with potential for developing new therapies against diabetes and cancer.
In pharmacology, it is crucial to understand the complex biological responses that drugs elicit in the human organism and how well they can be inferred from model organisms. We therefore identified a large set of drug-induced transcriptional modules from genome-wide microarray data of drug-treated human cell lines and rat liver, and first characterized their conservation. Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system. We then illustrate the utility of conserved and cell-type-specific drug-induced modules by predicting and experimentally validating (i) gene functions, e.g., 10 novel regulators of cellular cholesterol homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of α-adrenergic receptor, peroxisome proliferator-activated receptor and estrogen receptor. Taken together, the identified modules reveal the conservation of transcriptional responses towards drugs across cell types and organisms, and improve our understanding of both the molecular basis of drug action and human biology.
cell line models in drug discovery; drug-induced transcriptional modules; drug repositioning; gene function prediction; transcriptome conservation across cell types and organisms
Protein–side effects associations are identified by integrating drug–target data with side effects information from drug labels. Benchmarking against the literature and validation with an in vivo mouse model shows that these pairs correspond to causal relations.
For more than half of the investigated side effects, we can predict causal proteins.Off-targets contribute slightly more to the explained side effects than main targets.With the current data, we are most successful in explaining the side effects of drugs that target G protein-coupled receptors.Activation of HTR7 causes hyperesthesia in mice, explaining a side effect of triptan drugs.
Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug–target relations to identify overrepresented protein–side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.
computational biology; drug targets; side effects
When stressed by metal depletion, budding yeast adopt an asymmetric division pattern whereby vacuoles are maintained within dividing mother cells while the vacuoles-deprived daughter cells arrest division. This linear growth mode represents a bet-hedging strategy beneficial at the population level.
Budding yeast restricts division to a subpopulation of mother cells when metal is depleted.This population splitting into dividing mothers and arrested daughters implements a bet-hedging strategy beneficial for population long-term survival.Proliferation is limited by the availability of vacuoles, which are asymmetrically segregated to mother cells in a WHI5-dependent manner.Asymmetric resource distribution increases population growth under limiting conditions, defining a novel stress-response strategy.
We report that when budding yeast are transferred to low-metal environment, they adopt a proliferation pattern in which division is restricted to the subpopulation of mother cells which were born in rich conditions, before the shift. Mother cells continue to divide multiple times following the shift, generating at each division a single daughter cell, which arrests in G1. The transition to a mother-restricted proliferation pattern is characterized by asymmetric segregation of the vacuole to the mother cell and requires the transcription repressor Whi5. Notably, while deletion of WHI5 alleviates daughter cell division arrest in low-zinc conditions, it results in a lower final population size, as cell division rate becomes progressively slower. Our data suggest a new stress-response strategy, in which the dilution of a limiting cellular resource is prevented by maintaining it within a subset of dividing cells, thereby increasing population growth.
budding yeast; nutrients limitation; phenotypic diversity; zinc
An experimental-computational approach is applied to dissect the contribution of specific transcription factor-mediated versus global growth-dependent regulation to bacterial gene expression, and obtain a quantitative understanding of dynamic adaptations in arginine biosynthesis of E. coli.
We present a model-based approach to quantitatively dissect simultaneous contributions from specific transcription factors and the global growth status to bacterial gene expression, based on parameter inference from GFP-based promoter activity measurements.We show that growth rate can be used to predict the unregulated expression baseline of a gene, since growth rate dependence of global regulation occurs both in steady state and during transient changes in growth rate.We obtain a quantitative understanding of both specific and global regulation in arginine biosynthesis, as demonstrated by accurate model-based predictions of complex transient gene-expression responses to simultaneous perturbation in growth rate and arginine availability.We uncover two principles of joint regulation of the arginine biosynthesis pathway: (i) specific regulation by repression dominates in steady metabolic states and (ii) global regulation sets the maximal expression reachable during transition between steady metabolic states.
Gene expression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional—but often neglected—layer of complexity in gene expression. Here, we develop an experimental-computational approach to dissect specific and global regulation in the bacterium Escherichia coli. By using fluorescent promoter reporters, we show that global regulation is growth rate dependent not only during steady state but also during dynamic changes in growth rate and can be quantified through two promoter-specific parameters. By applying our approach to arginine biosynthesis, we obtain a quantitative understanding of both specific and global regulation that allows accurate prediction of the temporal response to simultaneous perturbations in arginine availability and growth rate. We thereby uncover two principles of joint regulation: (i) specific regulation by repression dominates the transcriptional response during metabolic steady states, largely repressing the biosynthesis genes even when biosynthesis is required and (ii) global regulation sets the maximum promoter activity that is exploited during the transition between steady states.
expression machinery; modelling; synthetic biology; transcriptional circuit; transcriptional regulation
A systems analysis of immune biomarkers in 89 young and older adults revealed age-dependent and age-independent features, including markers of apoptosis that correlated with antibody responses to a seasonal influenza vaccine.
Influenza hemagglutinin peptide arrays reveal age-associated effects that correlate with both pre-existing and vaccine-induced antibody titers.Age-dependent and age-independent baseline immune parameters correlate with and substantially predict the serological response to a seasonal influenza vaccine.Soluble FasL and gene modules associated with apoptosis are predictors of the serological response to an influenza vaccine, which was abrogated in Fas-deficient mice.
Despite the importance of the immune system in many diseases, there are currently no objective benchmarks of immunological health. In an effort to identifying such markers, we used influenza vaccination in 30 young (20–30 years) and 59 older subjects (60 to >89 years) as models for strong and weak immune responses, respectively, and assayed their serological responses to influenza strains as well as a wide variety of other parameters, including gene expression, antibodies to hemagglutinin peptides, serum cytokines, cell subset phenotypes and in vitro cytokine stimulation. Using machine learning, we identified nine variables that predict the antibody response with 84% accuracy. Two of these variables are involved in apoptosis, which positively associated with the response to vaccination and was confirmed to be a contributor to vaccine responsiveness in mice. The identification of these biomarkers provides new insights into what immune features may be most important for immune health.
aging; apoptosis; influenza; systems immunology; vaccinology
This study shows that, in bacteria grown in the laboratory, there is little correlation between when genes are important for fitness and when they are more highly expressed. Most genes thus appear to be regulated by signals that are not related to their function.
Many bacterial genes are expressed when they are detrimental to fitness.Most genes are not upregulated when they are important for fitness.Even biosynthetic genes are often not downregulated when they are not needed (except in E. coli).Genes with closely related functions often have different expression patterns.
Gene regulation in bacteria is usually described as an adaptive response to an environmental change so that genes are expressed when they are required. We instead propose that most genes are under indirect control: their expression responds to signal(s) that are not directly related to the genes' function. Indirect control should perform poorly in artificial conditions, and we show that gene regulation is often maladaptive in the laboratory. In Shewanella oneidensis MR-1, 24% of genes are detrimental to fitness in some conditions, and detrimental genes tend to be highly expressed instead of being repressed when not needed. In diverse bacteria, there is little correlation between when genes are important for optimal growth or fitness and when those genes are upregulated. Two common types of indirect control are constitutive expression and regulation by growth rate; these occur for genes with diverse functions and often seem to be suboptimal. Because genes that have closely related functions can have dissimilar expression patterns, regulation may be suboptimal in the wild as well as in the laboratory.
bacterial evolution; gene regulation; optimal regulation
Loss of collagen VII causes recessive dystrophic epidermolysis bullosa. Quantitative proteomics analysis of the extracellular matrix and secretome of human fibroblasts derived from pathologically altered skin reveals a global remodelling of the cellular microenvironment.
A global analysis of the microenvironment of human skin fibroblasts was carried out to reveal disease-related alterations in the extracellular proteome.The loss of collagen VII causes a deregulation of the basement membrane and dermal matrix proteome.Post-translational modifications of secreted proteins were altered in fibroblasts from recessive dystrophic epidermolysis bullosa samples.Metalloproteases displayed reduced activity and turnover in collagen VII-deficient cells.
The mammalian cellular microenvironment is shaped by soluble factors and structural components, the extracellular matrix, providing physical support, regulating adhesion and signalling. A global, quantitative mass spectrometry strategy, combined with bioinformatics data processing, was developed to assess proteome differences in the microenvironment of primary human fibroblasts. We studied secreted proteins of fibroblasts from normal and pathologically altered skin and their post-translational modifications. The influence of collagen VII, an important structural component, which is lost in genetic skin fragility, was used as model. Loss of collagen VII had a global impact on the cellular microenvironment and was associated with proteome alterations highly relevant for disease pathogenesis including decrease in basement membrane components, increase in dermal matrix proteins, TGF-β and metalloproteases, but not higher protease activity. The definition of the proteome of fibroblast microenvironment and its plasticity in health and disease identified novel disease mechanisms and potential targets of intervention.
disease proteomics; extracellular matrix (ECM); mass spectrometry; MMP14; primary human fibroblasts
A high-resolution map of human phosphorylation networks was constructed by integrating experimentally determined kinase-substrate relationships with other resources, such as in vivo phosphorylation sites.
High-quality kinase-substrate relationships (KSRs) were determined using an integrated approach that combines protein microarray technology and bioinformatics analysis.Phosphorylation motifs were predicted for 284 human kinases, representing 55% of the human kinome.A high-resolution map of human phosphorylation networks was constructed that connects 230 kinases to 2591 in vivo phosphorylation sites in 652 substrates.A new role for PKA downstream of Btk (Bruton's tyrosine kinase) during B-cell receptor signaling was discovered based on KSRs identified in the phosphorylation networks.
The landscape of human phosphorylation networks has not been systematically explored, representing vast, unchartered territories within cellular signaling networks. Although a large number of in vivo phosphorylated residues have been identified by mass spectrometry (MS)-based approaches, assigning the upstream kinases to these residues requires biochemical analysis of kinase-substrate relationships (KSRs). Here, we developed a new strategy, called CEASAR, based on functional protein microarrays and bioinformatics to experimentally identify substrates for 289 unique kinases, resulting in 3656 high-quality KSRs. We then generated consensus phosphorylation motifs for each of the kinases and integrated this information, along with information about in vivo phosphorylation sites determined by MS, to construct a high-resolution map of phosphorylation networks that connects 230 kinases to 2591 in vivo phosphorylation sites in 652 substrates. The value of this data set is demonstrated through the discovery of a new role for PKA downstream of Btk (Bruton's tyrosine kinase) during B-cell receptor signaling. Overall, these studies provide global insights into kinase-mediated signaling pathways and promise to advance our understanding of cellular signaling processes in humans.
phosphorylation; signaling networks; systems biology
A new genome-scale metabolic reconstruction of M. pneumonia is used in combination with external metabolite measurement and protein abundance measurements to quantitatively explore the energy metabolism of this genome-reduce human pathogen.
We established a detailed biomass composition for M. pneumoniae, thus allowing for growth simulations.Using our metabolic model, we corrected the metabolic network topology and the functional annotation of key metabolic enzymes.M. pneumoniae, unlike other laboratory-grown bacteria, uses a high fraction of energy (up to 89%) for cellular maintenance and not for growth.Simulating different growth conditions as well as single and double mutant phenotypes, we analyzed pathway connectivity and the impact of gene deletions on the growth performance of M. pneumoniae, highlighting the limited adaptive capabilities of this minimal model organism.
Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.
biomass composition; energy metabolism; in silico knock-outs; metabolic modeling; Mycoplasma pneumonia
The plant stem cell regulator WUSCHEL is shown to repress differentiation-promoting transcription factors. This regulatory network is analyzed with a computational model of the three-dimensional shoot stem cell niche and a combination of genetic perturbation and live imaging.
We find that the transcription factor (TF) WUSCHEL (WUS) directly binds to the promoters and represses a group of genes including key TFs involved in differentiation thus keeping them repressed in the stem cells of the plant shoot, a mechanistic logic that is similar to animal stem cell regulation.We use a three-dimensional computational model of the plant shoot stem cell niche to show that the WUS-mediated repression of the differentiation program along with the previously reported activation of its own negative regulator leads to a robust stem cell homeostasis in a dynamic growth environment.Live imaging of target genes upon transient manipulation of WUS levels is combined with model perturbations to validate the proposed network and to connect it with a large body of previous experimental work.
In animal systems, master regulatory transcription factors (TFs) mediate stem cell maintenance through a direct transcriptional repression of differentiation promoting TFs. Whether similar mechanisms operate in plants is not known. In plants, shoot apical meristems serve as reservoirs of stem cells that provide cells for all above ground organs. WUSCHEL, a homeodomain TF produced in cells of the niche, migrates into adjacent cells where it specifies stem cells. Through high-resolution genomic analysis, we show that WUSCHEL represses a large number of genes that are expressed in differentiating cells including a group of differentiation promoting TFs involved in leaf development. We show that WUS directly binds to the regulatory regions of differentiation promoting TFs; KANADI1, KANADI2, ASYMMETRICLEAVES2 and YABBY3 to repress their expression. Predictions from a computational model, supported by live imaging, reveal that WUS-mediated repression prevents premature differentiation of stem cell progenitors, being part of a minimal regulatory network for meristem maintenance. Our work shows that direct transcriptional repression of differentiation promoting TFs is an evolutionarily conserved logic for stem cell regulation.
central zone; CLAVATA3; shoot apical meristem; stem cell niche; WUSCHEL
The Caenorhabditis elegans SH3 domain interactome was mapped and compared with the yeast SH3 interactome. Orthologous SH3 domain-mediated interactions are highly rewired, but the general function of the SH3 domain network is conserved between the two species
C. elegans Src homology 3 (SH3) domain interactome was mapped using stringent yeast two-hybrid, resulting in a total of 1070 interactions among 79 out of 84 worm SH3 domains and 475 proteins.SH3 domain binding specificities were profiled for 36 worm SH3 domains using peptide phage display.The yeast and worm SH3 domain interactomes are significantly enriched in endocytosis proteins, but the specific interactions mediated by orthologous SH3 domains are highly rewired.Using the worm SH3 interactome, we identified new endocytosis proteins in worm and human.
Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form.
network evolution; phage display; protein interaction conservation; SH3 domains; yeast two-hybrid